Analytic system for automatically combining advertising and content in media broadcasts

ABSTRACT

An analytic platform, article of manufacture, system, computer-readable medium, and method for selecting and inserting advertisements for delivery to a content viewing device. A plurality of advertising metrics are generated from data originating from a plurality of content viewing devices. Then, an advertisement is selected for presentation along with content directed to one of the content viewing devices, the advertisement being selected based on the advertising metrics. Once selected, the advertisement is added to the content for delivery to said one of the content viewing devices.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a divisional application of U.S. patentapplication Ser. No. 14/922,681, filed Oct. 26, 2015, the entirecontents of which are hereby incorporated in their entirety.

BACKGROUND Field

The present disclosure relates generally to information management inmedia broadcasting and advertisement insertion, and more particularly,using analytic data to automatically select and insert targetedadvertisements in combination with media content leveraging multipleanalytic sources to derive return-on-investment (ROI) results forcampaigns across all platforms including connected TV, web, mobile andsocial platforms.

Background

Media content providers, such as national television networks andtelevision station groups, have evolved to serve the demand for onlineviewing across various formats. Consequently, in addition to regulartelevision broadcasts of programs, the same content may be streamed overthe internet as video on demand and/or live streaming. Examples ofdelivery formats include over the top (OTT) bypassing typical “managedservices” such as cable, satellite and IPTV infrastructure that can besubscription and/or transaction based or ad supported, online videoplatforms (OVP) such as YouTube, and TV Everywhere used by “managedservices” providers to provide their subscribers access to their contenton connected TV, web and mobile devices for both live and pre-recordedbroadcasts.

Traditional approaches to advertising and monetization are becomingineffective and outdated due to the evolving manner in which media ispresented to viewers.

SUMMARY

A method, article of manufacture, system, apparatus, andcomputer-readable medium are provided to enable an analysis of anoptimized return on investment for advertisement campaigns and ofcontent creation in order to determine an effective combination ofadvertisement placement and content on the best combination of deliveryplatforms. Advertising may be served in live streams, “as-live” such aschannel playout and/or on-demand. Advertising may be of a selectduration that best serves the delivery platform of choice, time of day,content type that it is being associated with and targeted as determinedby the campaign objectives and profile definition.

Aspects are provided that gather all sources of analytic data to be usedto analyze, derive and deliver the best ROI campaign results foradvertisers, allow broadcasters to provide the best creative programmingand determine the best combination of platforms to deliver, monitor,report and monetize results and target both advertising and specificcontent on a unique, per viewer basis. Different algorithms may be usedto provide suitable analysis for maximizing ROI, and different datagathering methods may be employed to provide the basis for analysis.Beyond inserting existing content, ROI can be increased further byresponding to the data analysis with personally created contentincluding, but not limited to, keyed in coupons, or purchase incentives,as web-links or email subscription, either on-screen, or in traditionallower third, or pillar box location, personalized menus of programchoices, or automatically selected programs feeds, based on genre andpsychographic data profiles.

The method and system may use analytic data to automatically select andinsert targeted advertisements in combination with media contentleveraging multiple analytic sources to derive return-on-investment(ROI) results for campaigns across multiple platforms includingconnected TV, web, mobile and social platforms. An advertiser will thenbe able to create a campaign with the best combination of ad creative,content type and target platforms. The broadcaster will be able to gaininsights into content categories and type that best drive ROI thereforeproviding their advertising customers with the best campaign results.

Aspects may include means for generating a plurality of advertisingmetrics from data originating from a plurality of content viewingdevices, means for selecting an advertisement for content directed toone of the content viewing devices, the advertisement being selectedbased on the advertising metrics; and means for adding the selectedadvertisement to the content for delivery to said one of the contentviewing devices.

The means for selecting an advertisement may be configured to select theadvertisement from a plurality of advertisements. The means forselecting an advertisement may be configured to select the advertisementbased on any of an advertising profile for the advertisement, metadatafor content with which the advertisement is inserted, and/or informationregarding the playout of the content at one of the content viewingdevices. At least a portion of the data may originate from any of asocial media application on one of the content viewing devices, a searchapplication on one, or more of the content viewing devices, and/or atelevision connected to a packet based network via any method of accesssuch as a set-top-box, cable modem access, smart-tv internet accessbuilt into the TV itself, or any other interact access method.

Aspects may further include any of means for deriving return oninvestment for adding the selected advertisement to the content, thereturn on investment being derived from the advertising metrics, meansfor deriving pricing for adding the selected advertisement to thecontent, the pricing being derived from the advertising metrics, meansfor creating content based on the advertising metrics and/or means forproviding specific content based on the advertising metrics. Advertisingmetrics may include a quality of experience (QoE) associated with eachof the content viewing devices.

Aspects may further include means for deriving return on investment foradding the selected advertisement to the content, the return oninvestment being based on one or more of the quality of experienceassociated with said one of the content viewing devices, the measurableactions, such as web link clicks, on said one of the content device, andthe audited purchase behavior measure by the commissioning associatedwith a purchase connected to the web-link, or coupon enabledtransaction.

Additional advantages and novel features of these aspects will be setforth in part in the description that follows, and in part will becomemore apparent to those skilled in the art upon examination of thefollowing or upon learning by practice of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example a system 100 for automatically selectingadvertisements for delivery along with media content in accordance withaspects presented herein.

FIG. 2 is a conceptual data flow diagram illustrating the data flowbetween different means/components in an example system in accordancewith aspects presented herein.

FIG. 3 is a conceptual data flow diagram illustrating the data flowbetween different means/components in an example system in accordancewith aspects presented herein.

FIG. 4 is a flow chart of an example method for managing advertising inmedia broadcasts in accordance with aspects presented herein.

FIG. 5 is a flow chart of an example method for managing advertising inmedia broadcasts in accordance with aspects presented herein.

FIG. 6 is a diagram illustrating an example of a hardware implementationfor a processing system in accordance with aspects presented herein.

FIG. 7 illustrates an example national and affiliate system inaccordance with aspects presented herein.

DETAILED DESCRIPTION

The detailed description set forth below in connection with the appendeddrawings is intended as a description of various configurations and isnot intended to represent the only configurations in which the conceptsdescribed herein may be practiced. The detailed description includesspecific details for the purpose of providing a thorough understandingof various concepts. However, it will be apparent to those skilled inthe art that these concepts may be practiced without these specificdetails. In some instances, well known structures and components areshown in block diagram form in order to avoid obscuring such concepts.

Certain aspects of video production systems will now be presented withreference to various apparatus and methods. These apparatus and methodswill be described in the following detailed description and illustratedin the accompanying drawing by various blocks, components, circuits,steps, processes, algorithms, etc. (collectively referred to as“elements”). These elements may be implemented using electronichardware, computer software, or any combination thereof. Whether suchelements are implemented as hardware or software depends upon theparticular application and design constraints imposed on the overallsystem.

By way of example, an element, or any portion of an element, or anycombination of elements may be implemented with a “processing system”that includes one or more processors. Examples of processors includemicroprocessors, microcontrollers, digital signal processors (DSPs),field programmable gate arrays (FPGAs), programmable logic devices(PLDs), state machines, gated logic, discrete hardware circuits, andother suitable hardware configured to perform the various functionalitydescribed throughout this disclosure. One or more processors in theprocessing system may execute software. Software shall be construedbroadly to mean instructions, instruction sets, code, code segments,program code, programs, subprograms, software components, applications,software applications, software packages, routines, subroutines,objects, executables, threads of execution, procedures, functions, etc.,whether referred to as software, firmware, middleware, microcode,hardware description language, or otherwise.

Accordingly, in one or more examples, the functions described may beimplemented in hardware, software, firmware, or any combination thereof.If implemented in software, the functions may be stored on or encoded asone or more instructions or code on a computer-readable medium.Computer-readable media includes computer storage media. Storage mediamay be any available media that can be accessed by a computer. By way ofexample, and not limitation, such computer-readable media can comprise arandom-access memory (RAM), a read-only memory (ROM), an electricallyerasable programmable ROM (EEPROM), compact disk ROM (CD-ROM) or otheroptical disk storage, magnetic disk storage or other magnetic storagedevices, combinations of the aforementioned types of computer-readablemedia, or any other medium that can be used to store computer executablecode in the form of instructions or data structures that can be accessedby a computer.

Advertising revenue for content providers may be obtained fromadvertisers for advertising campaigns, e.g., with fixed budgets. Contentproviders may improve advertising sales by demonstrating an accurate andoptimized return on investment (ROI) for such advertising campaigns.Moreover, demand for advertising may be increased by effective adselection and placement, and creative content that draws persistentviewers. Traditional methods for determining effective advertisementplacements and advertisement pricing are becoming obsolete with thecombined delivery of television programming and online streaming. Inaddition, different target groups have various viewing preferences anddifferent responses to advertisement types, further complicatingmanagement of advertising sales.

As described herein, analytics may be a key driver for broadcasters. Ananalysis of multiple data sources, certain types of which are referredto as big data, may assist broadcasters in calculating an ROI foradvertisement agencies. Such an ROI may be predicted (pre-sales) for usein filling advertisement spots in a broadcast or post-sales in order toshow the actual benefit derived from the advertisement/advertisementcampaign.

Metadata, e.g., metadata associated with media content, may be processedthroughout the broadcast production chain and may be used in combinationwith the analytics as well as traffic and billing information in orderto generate more accurate ROI metrics for selling ad avails, e.g.,advertisement spots in a broadcast, to ad agencies.

An automated process enables an accurate and up to date calculation andallows advertising metrics to be continually updated. The analytics maybe generated using data from a number of sources, including data mined,or received, from an OVP video player client on content viewing devices.Among other types of content viewing devices, this data may be receivedfor web, mobile, or connected TVs. For example, OVP/OTT TV Everywhere(e.g., authenticated streaming or authenticated video on-demand) mineanalytic data and return the data, e.g., to an analytics system. Thisanalytics system may be a part of a broadcast system. The receivedanalytic data may be analyzed, reported, and used to generateadvertising metrics for use in advertisement selection and advertisementsales. Through an automated process for calculating an ROI, advertisingmetrics may be generated and maintained and used to decide a best fitplacement for an advertisement.

In addition calculating and reporting an ROI for advertisement placementfor advertisers, aspects may further include selecting and/or generatingbest fit content and its associated ROI for broadcasters. This data,analyzed in combination with content metadata, enables an identificationof content that works best with a particular advertisement anddemographic along with the pricing information from traffic & billing.This may include an automatic calculation of an ROI for the broadcasterand/or potential advertiser.

As presented herein, analytics may also be used in video streamingoptimization. For example, Internet infrastructure and CDNs may bemonitored along with website and application performance to determine aquality of experience (QoE) at a content viewing device. This QoE datamay be collected by the analytics system and used to identify andreroute video streams in order to improve or optimize QoE. For example,video streams may be rerouted through the paths of least resistanceand/or paths with a highest level of performance. The use of such anautomated process provides an analytics platform that provides vendorssignificant value because QoE is a key metric to drive more consumerviewership and higher cost per impression (CPI) or cost per thousandimpressions (CPM).

Aspects provided herein provide an article of manufacture, such as ananalytics system providing an intelligent, automated content andadvertisement selection and sales management solution.

Aspects include the generation and maintenance of advertising metricsused to automatically drive advertisement decisions and insertion into acontent transmission. Advertising metrics may be generated usinganalytics and data from OVP, OTT, or TV Everywhere, etc. type contentviewing devices. Advertising metrics may be generated and maintainedusing analytics and data from social media video publishing. Such socialmedia data may include measurements of pre-production, production andpost campaign impact illustrating the effectiveness of at least oneparticular campaign throughout its process as compared to other contentand served advertisements.

Aspects may include the generation and maintenance of advertisingmetrics for use in automatically performing an ROI analysis foradvertisement pricing and sales. Performance metrics may be received andused to update the advertising metrics. Such performance measurementsmay include, e.g., information regarding demographics, geo-location,client profiles, content served with/adjacent to the advertisement, timeof day of the advertisement, advertisement category type, such as“exclusive”, “targeted” or “non-targeted,” whether the content was livestreaming or on-demand, sources, i.e. broadcaster website, mobile app,connected TV and/or syndicated sites and “creative”, i.e. identifyingcreative aspects of the content and/or advertisement that evoked apositive response such as selecting suggested programming or respondingto commissionable advertising. Pricing information and analytics may bereceived and used to update the advertising metrics. Pricing data mayinclude, e.g., data derived from historical performances based ondifferent pricing models. The analytics system may use this historicalpricing information to automatically determine a best pricing ROI for anadvertisement/advertisement campaign. For example, an optimum pricingROI may be determined for a specific content type, creative andplacement.

Aspects may include the generation and maintenance of advertisingmetrics for use in automatically driving content creation, selection andprogramming mix. For example, data regarding historical programming andsales may be used to automatically identify and prioritize the topicsthat best perform for both viewership and revenue. This identificationmay be automatically generated and used in a broadcast system to triggerthe creation of content for the identified topics. The identificationand prioritization of content topics may also be based on social mediainformation. For example, historical social media campaign metrics maybe used to automatically identify topics or story categories performsbest through certain social media campaigns and sites. Examples ofsocial media include, among others, social networks, blogs, businessnetworks, enterprise social networks, forums, microblogs, photo sharing,products/services review, social bookmarking, social gaming, socialnetworks, video sharing and virtual worlds. Examples of social mediainclude, e.g., Facebook®, Twitter®, Pinterest®, Google+®, YouTube®,Texting, Interactive Voice Response (Call Ins), etc. The social mediainformation may identify not only topics that are trending, but may alsoindicate factors of engagement, demographic information for the peoplediscussing/viewing such social media content, etc.

Social media information may include pre-campaign, during campaign, andpost-campaign information. Such information may include a number of“likes,” “shares,” views, recalls, exposure, etc. for each period oftime. A trending peak may be identified for a particular time.

Aspects may include the generation and maintenance of advertisingmetrics for use in automatically drive performance optimization.Performance optimization may be measured using QoE. Thus, aspects mayinclude, e.g., real time monitoring of infrastructure, CDNs, websites,mobile apps and connected TVs to optimize QoE. This may also includeautomating a selection in real time of which CDN to use forcontent/advertisement transmission/delivery, what bitrate to stream forany given video player based on pre-selected destination profiles, etc.Aspects may include continuous monitoring allowing automated dynamicchanges to Internet routing and best stream profile served to maximizeQoE. This data and metrics can then be used to update the ROIcalculation as performance improves.

In addition to receiving QoE information for content viewing devices,viewer histories may be received from a video player on a contentviewing device.

The analytics and metrics involved in these determinations may beautomatically updated on an ongoing basis. Thus, data may continually bereceived and used to update the advertising metrics.

FIG. 1 illustrates example aspects of a system 100 for automaticallyselecting advertisements for delivery along with media content. System100 may also be configured to identify content for creation.

A media production component 10 creates, stores, and/or provides mediacontent for delivery to any of a number of content viewing devices 50.Delivery of media content is also referred to herein as playout ortransmission of such content.

Media production includes the production of any and all forms of mediaor multimedia. A media production, also referred to herein as “mediacontent” or “content” includes, but is not limited to, news programs,television programming (such as, documentaries, situation comedies,dramas, variety shows, interviews, or the like), sporting events,concerts, infomercials, movies, video rentals, government content,public service content, corporate content, educational content, retailsales content, community content, or any other content. For example, andwithout limitation, media productions can include streaming videorelated to corporate communications and training, educational distancelearning, or home shopping video-based “e” or “t”-commerce. Mediaproductions may also include live or recorded audio (including radiobroadcast), video, graphics, animation, computer generated, text, andother forms of media and multimedia. Media productions may also includecombinations of the foregoing.

Media content may be presented in any of various formats, including,among others, live, OTT, OVP, VoD, TV everywhere, over social media, viatraditional broadcast, etc.

Media productions may be encoded and transmitted over a computernetwork, such as the global Internet, a local intranet, private virtualnetworks, or any other computer or communication network, medium, and/ormode, as well as over a traditional broadcast medium including,over-the-air, digital broadcast satellite (DBS), terrestrial cable, etc.As such, aspects presented herein support distributions to a recipient'stelevision, enhanced digital television, monitor or other display, aswell as over wired and/or wireless communication or computer networks(e.g., the World Wide Web) onto a personal computer (PC), laptop, mobiletablet, mobile phone, connected TV or other display or data processingor communication device. Thus content viewing devices 50 are illustratedas being various types of viewing devices.

“On-demand” content may be recorded or produced at a hosting facility(e.g., television station, radio station, newspaper, webcasting/onlineonly station, private homepage or web site, or other media “hosting”environment(s)), segmented, categorized, and indexed for retrieval andviewing.

“Live or as-live broadcast” may comprise a media production broadcastover traditional airwaves or other mediums (e.g., cable, satellite,etc.) to a television set. At the same time (or substantially the sametime), the production may be encoded for distribution over acomputer/communication network. The production for distribution over acomputer/communication network may be modified, e.g., segmented and/orenhanced. The traditional and network distribution modes/methods may besynchronized and transmitted substantially at the same time, or they canbe distributed at different times. The distribution can be live orrepurposed from previously stored media. The media production may bedistributed only via a traditional medium. In another example, the mediaproduction may be distributed only over a computer network. In anotherexample, they may be distributed multiple times, in a synchronizedand/or unsynchronized manner. In an example, the computer network mayinclude the Internet, and the enhanced media is formatted in hypertextmarkup language (HTML/HTML5) or other formats including but not limitedto Apple HLS, Microsoft Smooth Streaming, Adobe HDS and/or the approvedInternational standard, MPEG-DASH for distribution over the World WideWeb.

Advertisements may be presented to a viewer at a content viewing devicealong with the content.

Advertisements may include video or audio commercials; dynamic or staticdisplays; sponsorship advertisements; still images, public servicemessages; community messages; government messages; pre-roll, post-roll,mid-roll advertisements; active or passive advertisements; skyscrapers;email correspondence; or like forms of media and multimedia promotions.It is noted that the term “advertisement” as used herein includes anytype of message and content.

Video or audio commercials can be integrated into a media stream suchthat the commercial feed can be presented to the user while the userviews the media production. For example, the commercial feed can bepresented after one or more news stories, at the beginning of the mediaproduction, at the end, between scenes within a video production, or atany other place designated by the video producer/director or automatedthrough the intelligence of the system pre-programmed to specific rules,pre-determined profiles and historically driven and learned artificialintelligence.

The advertisements may also include banners (sometimes referred to as“display” advertising). A display, or banner, includes any combinationof text, graphics and other forms of media and multimedia that promotesa good or service, or otherwise provides information or an announcement.The display can be strictly descriptive, or include hypertext, a hotspot, or a hyperlink to open additional display, place an order, or senda request for additional information to the server of the hostingfacility or another server. The display can include a hyperlink to anypre-defined destination. The display can be a static display that onlydisplays the promotional advertisement. However, the display can also bean active display that blinks, spins, fades, and the like. The displaycan also be a scrolling display that includes a scroll bar that allowsthe user to move through contents of the display. Resizable displays canalso be used to allow the user to expand or enlarge the display toreceive more data. The aforementioned is a representative list ofdisplays that can be used with the present invention, it should beunderstood that any other type of display capable of promoting a productor conveying a message or content, including, but not limited to,displays developed with Macromedia® Flash™ or Macromedia® Shockwave®, orthe like, as would be apparent to one skilled in the relevant art(s),could be easily included and would not change the scope of theinvention.

The advertisements can also be active or passive. An activeadvertisement requires or permits interaction from the user, such asclicking-through, scrolling and the like. Passive advertisements aredisplayed and require no interaction from the user. Additionally, theadvertisements can take the form of pre-roll, mid-roll or post-rolladvertisements. Such advertisements may comprise, for example,commercials, displays, or the like that are transmitted to the displaydevice prior to the startup of the media production or served“server-side” such that the ad is delivered or streamed to the videoplayer already inserted or “stitched” together for both live andon-demand content applications.

Advertisements may be “exclusive,” “targeted” or “non-targeted,” forexample. Exclusive advertisements may be served with a specified topicor category. Exclusive advertisements may be, for example, served withon-demand media productions, and may be linked to a media production bya topic or category that has been established for the media production.Exclusive advertisements might not be rotated among otheradvertisements. As such, exclusive advertisements may be sold at apremium price, and the exclusive display, button, video, or the like isdisplayed with the specified topic or category throughout the durationof the linked media production or a segment thereof.

Targeted advertisements may also be served with a specified topic orcategory. However, unlike exclusive advertisements, targetedadvertisements may be rotated among other targeted advertisements. Inone example, display or button advertisements may be rotated in and outon a ten-second interval, although intervals of other durations arecontemplated by the invention. With respect to video or audio-streamingadvertisements, such advertisements may be rotated with other targetedstreaming advertisements. Targeted advertisements may also be sold at apremium price, but at a lower price than exclusive advertisements.

Non-targeted advertisements may be served without regard to a specifiedtopic or category, and may therefore be sold at a lower price thantargeted advertisements. Additionally, non-targeted advertisements arerotated among other non-target advertisements.

As such, aspects presented herein support all types of advertisementsthat can be transmitted over a client-server network to a displaydevice. In one example, as a video show is being transmitted, theadvertisements may be streamed at specified intervals and durations withthe video show. In an example, the advertisements may be presented onthe side panels of the same frame or window in which the video show isdisplayed. In another example, the advertisements may be streamed inseparate frames. In another example, the advertisements may be streamedprior to the display of the related segment video. The advertisementsmay also include a hyperlink to a web site for the sponsor of theadvertisement. Aspects presented herein may include any combination ofthe above.

Aspects presented herein enable advertisements, in various formats, tobe linked and integrated with a media production. Several methodologiesand/or techniques are available for selecting and integrating theadvertisements into the media production. The advertisements can beembedded directly into the media production as an introductory piece, ata break within the media production, and/or at the end of the mediaproduction. The parallel distribution of the advertisements can beimplemented by presenting the advertisement in another window, frame, orregion.

Linear advertisements may be located before, during (i.e., commercialbreaks), and after a media production. Linear advertisements may includeaudio and/or video commercials, public service announcements, and othercontents, as described above, that are served in series with the mediaproduction. Non-linear advertisements may be simultaneously displayedduring the presentation of media production. Non-linear advertisementsmay include displays, buttons, audio/video content, and the like thatare located in a separate region, frame, or window than the mediaproduction. Non-linear advertisements may support a combination ofserial and parallel servicing. In other words, non-linear advertisementsmay be served in parallel with the media production, but in series withother non-linear advertisements

In FIG. 1, system 100 includes an advertisement management component 20.This advertisement management component may include an ad bank 22 thatstores advertisements to be presented to viewers. In addition to theadvertisements, the advertisement management component 20 may comprisean advertising profile component 24 that stores an advertising profileassociated with each of the corresponding advertisements in the ad bank22.

An advertising profile for an advertisement may comprise, among otherprofile parameters, demographics, geographic location, client profiles,content topic, time of day, category type, live-streaming or on-demand,source, creative information. The category type may indicate whether theadvertisement is exclusive, targeted, non-targeted, etc. The source mayinclude, e.g., a broadcaster website, mobile application, connected TVand/or syndicated sites, etc. Creative information may include, e.g.,content category, type, source, origination date,author/editor/producer/director, or other metadata description, etc.

System 100 also includes an analytics system 30 that generates aplurality of advertising metrics from data originating from a pluralityof content viewing devices. Analytics system 30 may dynamically updateand maintain the plurality of advertising metrics based on informationreceived from any of a number of sources. At least a portion of the datamay originate from a social media application on one of the contentviewing devices. Thus, the analytics system 30 includes a social mediacomponent 36 that receives information from social media andincorporates the information into the advertising metrics. A portion ofthe data may originate from a television connected to a packet basednetwork. As one example, the social media module may track the number of“shares” or “likes,” where viewers have shared a viewed ad or contentclip with a friend. Information may be continually mined from videoplayers on the content viewing devices in order to providecontent/advertisement viewing history information to the analyticssystem.

Using the advertising metrics, advertisement media selection component31 may select media to be presented along with content directed to atleast one of the content viewing devices 50. In one example, theselected media may comprise content. In another example, the selectedmedia may comprise at least one advertisement. Playout component 33 mayadd the selected media to the content, e.g., from content received frommedia production component 10 for delivery to one of the content viewingdevices 50 via content delivery network (CDN) 40.

For example, an advertisement may be selected from one of the pluralityof advertisements stored in advertisement bank 22.

The selection of the media, whether content or advertisement, mayfurther be based on the advertising profile stored at advertisingprofile component 24 for the media. The analytics system 30 includes anadvertising profile component 32 that receives/accesses the advertisingprofile information. The advertising profile may include, e.g., abudget, creative information, demographics for a target audience, timeof day parameters, delivery platform parameters, social media platformparameters, geo-location targets, content restrictions, etc. Theanalytics system 30 may use its generated advertising metrics in orderto analyze advertising profiles for a plurality of advertisements in thead bank and to determine an advertisement that will provide a predictedoptimum ROI. An ROI is a calculation of the benefit to the advertiserresulting in their investment in advertising.

For example, the ROI measurement may be based on an increase in salesresulting from an amount paid for advertisements or it may be based on“reach” of the targeted audience to achieve a “branding” objective orbased on targeted consumer actions such as viewing duration, continuedviewing during changes in programming and insertion of advertising,social media sharing parameters, click-throughs for engagement goals.The ROI may include an analysis of any of the amount of exposure to theadvertisement, exposure for a particular demographic, and an amount ofsales after exposure. The ROI may also consider an amount of actioncreated. The ROI may identify a number of times that the advertisementwas viewed in completion and a number of partial views for theadvertisement. Partially viewed advertisements may be scaled in the ROIcalculation.

The analysis may further include an analysis of the content for playout,e.g., the content to which an advertisement is being selected fordelivery to a display device. Thus, analytics system includes contentcomponent 38 that receives content information for use in the selectionof the advertisement. For example, content for playout may compriseassociated metadata for the content. The metadata may include, amongothers, a content type, show and/or story title, producer/director,keywords, historical demographics, viewing times and platform of choicefor like content, content association restrictions, rights management,syndication parameters, duration information, content rating, etc. Thus,the advertisement selection component 31 may select the advertisementfurther based on the metadata for the content that will be presentedwith the advertisement.

In addition to assisting in the selection of an advertisement, contentcomponent may use the advertising metrics and other information gatheredby the analytics system in order to create content. For example, thecontent component may identify topics, distribution platforms of choice,social media “viral” sharing and trending data, content types(interview, editorial, documentary, etc.) and demographic profile, ofparticular interest or of particular benefit when used in combinationwith advertisements. This identification can be communicated to mediaproduction component for creation of the content. Thus, the analyticssystem not only enables a dynamic optimization of the selection of anadvertisement, but also enables the creation of content to form anoptimum combination of content and advertisement.

The analytics system 30 may also receive information regarding a contentviewing device 50 to which the content is being delivered, e.g., viaviewing device component 37. Such information may include a QoE 38associated with each of the content viewing devices to which the contentis directed. A QoE may comprise, e.g., a quality of service (QoS)performance measurement associated with, jittering, blockiness,artifacts and buffering, metrics. Viewing device information 39 may alsocomprise QoE type information such as information regarding theperformance of infrastructure, CDNs, websites, mobile applications,content viewing devices, etc. involved in the transmission and displayof content and advertisements. Viewing device information may alsoinclude other information.

For example, a local server may generate and store metadata in responseto the viewer behavior and treatment of the media content, including thetime of day, duration of viewing, context, category, number of views andrepeated views per client, number of downloads, consumer demographics,media rotation (e.g., live or on demand), and the like. The metadata maybe generated by period, show, topic, account, or the like. Page viewsand click-throughs represent another type of collected data. Page viewsrefer to the actual number of web pages received by an online user.Click-throughs refer to the online user actually clicking on, forexample, a display advertisement to get more information on theadvertised product or acknowledge that the user has considered theadvertisement. The data collected in response to page views andclick-throughs include statistical data with respect to consumerdemographics, linked topic and show metadata, download time of day,medium of advertisement, type of advertisement, and the like.

The media selection component 31 may select the media, e.g.,advertisement or content, further based on such information regardingthe viewing device.

The analytics system may include an ROI component 34 configured toderive a return on investment for adding the selected advertisement tothe content. The return on investment may be derived from theadvertising metrics. The ROI may be based at least in part on the QoEassociated with the content viewing devices.

The analytics system 30 may also include a pricing component 35configured to derive prices for adding the selected media, e.g.,advertisement or content, to the content. The pricing may be derivedfrom the advertising metrics. For example, data derived from historicalperformances based on different pricing models may be used in thedetermination of a best pricing ROI for a specific content type,creative, placement, etc.

System 100 may be connected to a media broadcast facility as well as tovarious servers including content delivery servers, ad servers, socialmedia servers, application servers, and at least one local host servervia a network.

Media content may be produced at such a media broadcast facility for atelevision broadcast, online streaming, and other types of delivery.Content may be generated at a live feed or may include prerecordedcontent. Such prerecorded content may include segments of a livebroadcast.

In a case where media broadcast facility is a parent network producing anational broadcast, content viewing devices may receive the broadcastfrom a local host server used by a local network affiliate, which may beconfigured to insert ads in the media broadcast tailored to profiles anddemographics corresponding to the local viewing audience. FIG. 7illustrates a system with a national system and local affiliate systems.Advertisements may originate from advertisement bank 22 at the mediabroadcast facility for ad slots reserved for the national broadcast,while local ads may originate from ad servers and/or ad banks of a localhost server.

Social media servers may be used by the broadcaster for online streamingof content and ads, such as for example, a video clip or segment shownon broadcaster's Facebook page.

Application servers may be used by the broadcaster when video on demandrequires an application to display the video on the content viewingdevices, in which case the client may pull the application code from theapplication server for a one-time playback use, or the application maybe cached at the content viewing device for further online videoplaybacks.

FIG. 2 illustrates a workflow through a system comprising an analyticssystem. The analytics system may include aspects similar to thosedescribed in connection with analytics system of FIG. 1.

Content creation and delivery may begin at a media content source. Thismay include, e.g., a network or a television station, among othersources of media content. Dashed line 202 illustrates an example networkperimeter. The media content source may create content at 204. Contentmay comprise a live production and/or other content for playout.Segments of a live production may be stored and presented to viewers ata later time. The content undergoes encoding and transcoding at 208 fordelivery to at least one content viewing device, e.g., consumer(s) 250via contend delivery network 210.

In addition to the content, advertisements may be selected for deliveryto the content viewing device. Online ad platform 212 may receive thecontent stream and identify segment demarcations, advertisement breaks,or other available spots for advertisements. These available sports arealso referred to herein as ad avails. This information may be providedto online ad services 214 in order to select an advertisement forinsertion/delivery along with the content. As described above, thecontent may include metadata. The content metadata may be received andprovided to the online ad services 214 for use in selecting anadvertisement. In one example, the online ad platform may strip metadatafrom the content stream for use in selecting advertisements to bedelivered with the content.

Online ad services 214 may maintain continuously updated analytics aswell as providing reporting, reconciling, and decisioning regardingadvertisement selections and advertisement campaigns. Online ad services214 may include a decision engine that receives and uses an advertisingprofile and uses dynamically updated metrics in order to deliveradvertisements in an optimum manner.

FIG. 3 illustrates an example flow of information into the analyticssystem. The analytics system may then generate and/or update theadvertising metrics in order to select targeted advertising having ahighest ROI and QoE delivery. Additionally, content programming may beselected using the analytics system in order to create a content andtargeted advertisement combination that further increases the ROI andQoE.

FIG. 3 illustrates the analytics aspects that may be combined in acombined analytics system 312, e.g., in order to generate and updatemetrics for use in selecting advertisements to be presented at contentviewing devices with media content.

For example, content and advertisement analytics 302 may be formulatedand used to determine content and advertisement creation and selection.Such analytics may also be used to create or select a programming mix.In an automated manner, historical programming and sales may be used todefine and prioritize topics for media content and advertisements thatprovide the best performance for both viewership and/or revenue. Inaddition, ad styles, target profiles may be identified and prioritizedusing content and advertisement analytics. This may include accountingfor duration, placement, targeting, and messaging, among others. Thecontent and advertisement analytics may be used to identify a best ROIthrough a combination of both content and advertisements. For example,the best ROI may correspond to the best predicted return on payment foran advertisement or for an advertisement campaign.

Social media analytics 304 may receive, analyze, and search current, orrecent, information on social media. For example, the social mediaanalytics may monitor social media sources to identify trending topicsand to determine the effectiveness of previously displayedadvertisements. Social media pre-production, production, andpost-production advertisement feedback metrics used to drive viewershipmay be used to calculate both content and advertisement effectiveness.For example, the social media analytics may measure the effectiveness ofadvertisements using a number of data points, including, e.g., creative,content type, messaging, demographic, geographic location, social mediaplatform, time of day, etc. For example, various social media platformsmay be continuously monitored in order to identify trending topics. Theidentified trending topics may be used to select content and/oradvertisements for delivery to a content viewing device. Additionally,trending topics may be used to select content/type/creative for thecreation of content or advertisements.

Flow Optimization Analytics 306 may be used to continually updateperformance optimization of the advertisement being sent to the contentviewing device. This may include, e.g., real time monitoring ofinfrastructure, CDNs, websites, mobile applications, and connected TVsin order to determine an optimum QoE. This may further includeautomatically selecting a CDN with the least congestion for distributionof content/advertisements to a content viewing device for the bestperformance results. This may also include automatically selecting abitrate for the stream for any given video player based on pre-selecteddestination profiles. As well, continuous monitoring may allow automateddynamic changes to Internet routing and best stream profile in order tomaximize QoE. Additionally, these QoE metrics may then be used to updatethe ROI calculation as performance of the stream improves addressing“minimum” standards of acceptable performance for monetization.

Advertisement serving analytics 308 may be used to formulate theselection of advertisements and the dynamic insertion of suchadvertisement into streams of published content. This may include livemedia streams as well as VOD published content. Information for theadvertisement serving analytics 308 may be gathered, e.g., received,from content viewing devices themselves. For example, information may begathered from OVP and OTT TV players, from social media videopublishing, etc. Generated metrics for an advertisement or for anadvertisement campaign may be measured and compared to other content andadvertisements. By comparing their performance, advertising metrics maybe continuously updated. For example, the ROI calculation may becontinuously updated based on the gathered information. The metrics andROI calculation may further be optimized by comparing an advertiser's adtarget profile to these metrics and analyzing both a predictive ROI(pre-sales) and a real time result ROI (post sales).

Pricing and Sales Analytics 306 may be used to formulate an ROI analysisfor advertisement pricing and sales performance. Among others, suchanalytics may include metrics based on demographics, geographiclocation, client profiles, media content served, time of day, categorytype, live streaming versus on demand type content, source destination,etc. Pricing analytic data may be derived from historical performancebased on different pricing models in order to determine a pricing for aspecific content type, creative and placement that is estimated toprovide a best ROI. Similar to the other analytics, the pricing analyticdata may be continuously updated, e.g., using information from the otheranalytic sources, e.g., 302, 304, 308, and 310.

Thus, the analytics system 312 may merge data from any of the differentanalytics sources 302, 304, 306, 308, and 310 in order to generate asingle set of combined advertising metrics. The advertising metrics mayuse the data from the different sources to generate metrics forselecting advertisements predicted to have the best ROI and for addingthose selected advertisements to media content for delivery to a contentviewing device.

Additional tools may be provided that track the impact/effectiveness ofan advertisement or an advertisement campaign. The tools may provide aperformance based review, e.g., comparing an amount of sales to anamount paid for an advertisement campaign.

A combination of the analytics 302, 304, 306, 308, and 310 and sharingmetrics among different analytics components enables theselection/creation of programming and targeted advertising that ispredicted to have a highest ROI. Additionally, the consideration of QoEdelivery in combination with the other analytics allows a broadcast asignificant advantage.

FIG. 4 is a flowchart of a method 400 of selecting media, e.g.,advertisements or content, for addition to media content for delivery.The method may be performed, e.g., by a broadcast advertisementanalytics system, e.g., such as analytics system 30, 200, 312. At 402,the system generates a plurality of advertising metrics from dataoriginating from a plurality of content viewing devices, e.g., 50. Theseadvertising metrics may include, e.g., analytics to drive ad decisioningand dynamic insertion into live streams, VOD, OTT, on-demand, internetor mobile based content delivery, traditional broadcasts, etc.Information regarding published content may be gathered from OVP & OTTTV Everywhere Video Players as well as from “Social Media” videopublishing measuring campaign metrics with comparisons to other contentand served ads to “continuously” drive the development and update of theadvertising metrics that can be used to calculate an optimizedadvertising campaign.

Once generated, the advertising metrics may be stored, e.g., at 404.Optional aspects in FIG. 4 are illustrated with a dashed line.

At 406, the system selects media, e.g., an advertisement or content, forpresentation in connection with content directed to at least one of thecontent viewing devices. The media may be selected based on theadvertising metrics generated at 402. For example, an advertisement maybe selected from a plurality of potential advertisements.

At 408, the system, adds the selected media to the content for deliveryto the content viewing device(s). Once selected, the media, along withthe content, may be encoded/transcoded and transmitted to a contentdelivery network for transmission to the content viewing device. Wherethe selected media being selected is an advertisement, for example, thesystem may receive a transmission and use segment demarcations oradvertisement breaks in order to trigger the selection of anadvertisement.

In addition to receiving the advertising metrics generated at 402, thesystem may further receive an advertising profile for the media, e.g.,content or advertisement, at 410. The selection of the advertisement at406 may be further based on the advertising profile for the media. Anadvertisement target profile may be compared to metrics maximizingperformance, e.g., maximizing a ROI calculation. This comparison may bemade in order to generate predictive (pre-sales) and/or post sale ROI.Among others, the advertising profile may include e.g., any of a targetdemographic, geo-location, client profiles, content type, time of day,category type, live streaming or on-demand, source destination, price,etc.

The system may further receive metadata at 412 associated with contentfor delivery to the content viewing device. Among others, the metadatamay include, e.g., any of a content topic, time, date, demographic,creative, etc. When the system receives media content that will betransmitted to a content viewing device, in addition to using segmentdemarcations in order to identify advertisement breaks, the system mayalso strip/access metadata from the content. The advertisement may beselected, at 406, based further on the metadata for the content.

The system may further receive information regarding social media at414. Thus, at least a portion of the data may be originated from asocial media application on one of the content viewing devices. SocialMedia pre-production, production and post-production campaign feedbackmetrics to drive viewership may be used to calculate ad effectiveness,as well as content selection/creation. Various types of social mediainformation/data points may be received, e.g. regarding any of byvarious data points such as creative, content type, messaging,demographic, geo-location, platform (Facebook, Twitter, etc),time-of-day, etc. Thus, the selection of the advertisement at 406 mayfurther be based on the received social media information.

In addition to social media, at least a portion of the data used forgenerating the advertising metrics may originate from a televisionconnected to a packet based network.

The system may further receive content player information from each ofthe content viewing devices at 416. This may include informationregarding the content viewing device itself or about the quality ofplayout at the content viewing device, such as a bit rate, bufferinglevels, as well as other demographic information about the contentviewing device. This may also provide characteristics regarding theperson operating the content viewing device. This may include ageographic location, viewing/searching characteristics from the contentviewing device, etc. The advertisement may be selected at 406 basedfurther on the received QoE information. Thus, QoE analytics may be usedto automatically drive performance optimization with real timemonitoring of infrastructure, CDNs, websites, mobile apps and connectedTVs to optimize QoE. This may include automatically selecting which CDNto choose for delivery of the advertisement. In another example, abitrate may be automatically selected to stream for any given videoplayer based on pre-selected destination profiles. In addition,continuous monitoring of QoE at a content viewing device allowsautomatic dynamic changes to Internet routing and best stream profile inorder to maximize QoE. As well, these QoE metrics may then be used toupdate an ROI calculation as performance improves.

Thus, at least a portion of the data used to generate the advertisingmetrics at 402 may be obtained by mining analytic data at a video playeron a content viewing device, whether web based, mobile based, ortelevision based.

The system may further receive pricing or sales information at 418. Theselection of the advertisement at 406 may be further based on thereceived pricing or sales information. This allows the media selectionto be based on budget in addition to other metrics, such as advertisingprofiles, creatives, etc. Thus, the selection of the media may furtherinclude an analysis regarding ad pricing and sales performance. Thisanalysis may be further based on other received information, including,e.g., information such as demographics, geo-location, client profiles,content served, time of day, category type, live streaming or on-demandand source destination. Pricing analytic data may be derived fromhistorical performances based on different pricing models toautomatically determine a best pricing for a specific content type,creative and placement, for example.

The information received at any of 410, 412, 414, 416, and 418 may alsobe incorporated into the advertising metrics. For example, suchinformation may be used to generate the initial ad metrics and/or may beused to update the advertising metrics.

The metrics and received information may be used, not only to select anadvertisement for presentation at a content viewing device, but may alsobe used for the creation of content itself. Thus, the metrics andinformation may be used to identify a topic of interest or that wouldgenerate a maximum number of views or that would combine with anadvertisement to generate a maximum number of views to a particularaudience so that an optimum content/advertising combination may becreated. Thus, at 420, the system may use the advertising metrics andany of the received advertising profile, content metadata, social mediainformation, QoE metrics, and advertisement pricing information toidentify content for creation. This may include, e.g., identifyingtrending topics, topics of general interest, types of content, etc. thatare of particular interest to consumers.

The creation of content may be based on any of viewing performancemetrics, social media topic trend metrics, social media content sharingmetrics, and advertising performance metrics. Social media contentsharing metrics may include a quantity and/or duration of the sharing,e.g., minutes, hours, days, weeks, etc.

The content may be selected to be of interest to a maximum number ofcontent viewers or to a particular demographic of content viewers. Thecontent may be identified that will form a financially beneficialcombination with a particular advertisement or advertisement campaign.

Thus, the generation of content at 420, or the identification of contentfor generation, may include analyzing what combination of content andadvertisement works best, e.g., provides the highest ROI. Thus, contentmay be created and advertisements may be selected to form a content andadvertisement combination that maximizes an estimated ROI. This analysismay be broken down by demographics. Thus, the analysis may identify thecontent and advertisement combination that performs the best for aparticular demographic. This analysis may be used in order to identifycontent for creation. The identification of content may further be basedon an advertisement profile for a particular advertisement oradvertisement campaign, in order to create a combination of content withwhich such advertisements may be inserted in order to generate the bestROI for the advertisement or advertisement campaign.

The system may further derive a ROI at 422 for adding the advertisementto the content. The ROI may be derived, e.g., based at least in part onthe advertising metrics. The ROI may be a predicted ROI. Additionally,the system may monitor consumption and/or viewer feedback so that theROI may comprise a real-time result or “post-sales” ROI. The ROI may bederived from the advertising metrics, the advertising metrics includingmultiple analytics comprising at least two of content analytics,advertising analytics, social media analytics, quality of experienceanalytics, sales analytics, and pricing analytics.

This ROI may be determined at 422 not only for a particular display ofan advertisement, but for an advertisement campaign, as well. Thus, themethod may comprise tracking the impact/effectiveness of anadvertisement or an advertisement campaign. This may include making aperformance based analysis, e.g., comparing an amount of sales to anamount paid for an advertisement campaign. The analysis may includemeasuring content viewing, e.g., both traditional broadcast viewingand/or internet streaming. The analysis may also include measuring thepurchases by those same individuals or same demographic.

This information may be used along with the advertising metrics, theAdvertisers “Ad Target Profile”, and/or content metadata, to maximizingperformance. These aspects may also be used to generate both“predictive” (pre-sales) and “real time results” (post-sales) ROIreports.

The ROI may be based further on the QoE associated with the contentviewing device. The QoE may be monitored, and as QoE information isreceived, e.g., at 416, video and/or advertisement transmission may bererouted in order to maximize a QoE for the content viewing devices.This may be done, e.g., on a software as a service (SaaS) model. Inaddition to rerouting the transmission, an advertisement may be selectedbased on the monitored QoE information in order to drive performanceoptimization. This may include, e.g., real-time monitoring ofinfrastructure, CDNs, websites, mobile applications, and connectedtelevisions in order to optimize QoE for an advertisement/advertisementcampaign. Aspects may include automating the selection of any of a CDN,a bitrate for streaming for a given video player, etc. These selectionsfor the transmission may be based on pre-selected destination profiles.

Continuous monitoring allows automated dynamic changes to internetrouting and a best stream profile in order to maximize QoE. Thesemetrics can then be used to update the ROI calculation as performanceimproves. For example, these metrics can be used to update theadvertising metrics at 426. The updated advertising metrics may be usedto calculate an updated ROI.

Additionally, the system may derive pricing at 424 for adding theselected advertisement to the content, the pricing being derived, atleast in part, from the advertising metrics.

Although the ROI and pricing determinations are illustrated in a blockafter the selection of the advertisement, these aspects may be performedas a part of the selection at 406 of the advertisement itself.Additionally, the derived ROI and derived pricing may be incorporatedinto the advertising metrics. Thus, at 426 the system may update theadvertising metrics based on this new information.

The system may continue to monitor viewing of the advertisement and/orfeedback regarding the advertisement at 428. Feedback may be obtainedregarding the creative aspects of the advertisement. An analysisregarding the efficacy of the advertisement may also analyze the contextin which the advertisement was presented to the content viewing device.For example, the content with which the advertisement was presented maybe analyzed. For example, certain customer groups may respond to aparticular type of advertisement over another. Thus, this analysisallows the identification of the context in which the advertisements aremost effective.

The analysis may include an analysis of the effect for a target market.The analysis may include an analysis of whether the sales were made at ahigher product price, or whether the sales were discount driven.

This feedback information, along with other received data can be used toupdate the advertising metrics, e.g., at 426.

Thus, the advertising metrics are continually updated to reflect achanging content viewer environment into which advertisements will betransmitted. This includes not only QoE changes, but also addressesongoing changes in viewers' interests.

Although the advertising metrics are illustrated as being separate fromthe information regarding the advertising profile, social mediainformation, pricing information, QoE information, and content metadata,any of these sources of information may be used in generated and/orupdating the advertising metrics.

FIG. 5 illustrates a flowchart of aspects of a method 500 of selectingmedia, e.g., advertisements or content, for addition to media contentfor delivery. The method 500 may include the receipt of information froma number of sources and the generation of advertising metrics, asdescribed in detail in connection with FIG. 4. The same referencesnumbers are used for these sources of information and the generation,storage, and update of advertising metrics.

As illustrated in FIG. 5, once the advertising metrics are generated at402, an advertising profile for an advertising campaign may be receivedat 502. The profile may include information similar to that descried foradvertisement profile 410, and may include a price to be paid for theadvertising campaign. The advertising profile may be for a singleadvertisement or may comprise a plurality of advertisements. Theplurality of advertisements may differ in type, creative, demographic,geographic location for placement, etc.

At 504, ad avails may be received. The system may identify, for example,openings or opportunities for the insertion or delivery ofadvertisements and content. The ad avails provide an indication ofavailable advertisement placement positions, slots, etc. The system mayuse the information in the advertising campaign and the generatedadvertising metrics to determine an optimum placement ofadvertisements/content in order to generate an optimum ROI at 506. Forexample, the system may identify a placement for a single advertisementthat is predicted to generate the highest ROI for the price indicated inthe advertising profile. Similarly, the system may identify acombination of placements at a plurality of ad avails having a highestpredicted ROI for the price indicated in the advertising profile. Aswell, when the advertising profile includes a plurality ofadvertisements, the system may identify a combination of placements forthe plurality of advertisements that having a highest predicted ROI forthe price indicated in the advertising profile.

At 508, the system may also automatically add an advertisement/contentfrom the advertisement profile to content for delivery to a contentviewing device at the placement identified in 506.

Once the advertisement/content has been delivered to a content viewingdevice at 508, the system may monitor feedback and/or consumption at 510in order to update the advertising metrics at 426. Likewise, the systemmay update the determination of the advertisement placements at 506 forfuture ad avails based on the feedback received at 510.

An article of manufacture e.g., such as systems 100, 200, 300 mayinclude components that perform each of the blocks of the algorithm inthe aforementioned flowcharts of FIG. 4 or FIG. 5. As such, each blockin the aforementioned flowcharts of FIG. 4 and/or FIG. 5 may beperformed by a component and the article of manufacture may include oneor more of those components. The components may be, e.g., one or morehardware components specifically configured to carry out the statedprocesses/algorithm, implemented by a processor configured to performthe stated processes/algorithm, stored within a computer-readable mediumfor implementation by a processor, or some combination thereof.

FIG. 6 is a diagram 600 illustrating an example of a hardwareimplementation for an article of manufacture employing a processingsystem 614. The processing system may include a data receptioncomponent, e.g., configured to receive data relating to advertisingprofiles, content metadata, social media information, QoE measurements,pricing information, advertisement campaigns, feedback regardingadvertisement or content, ad avails, consumption related toadvertisements, etc. The processing system may include an advertisementand/or content transmission component 622 that adds an advertisement tocontent for delivery to a content viewing device. The processing systemmay include an advertising metric generation component 624 thatgenerates and updates advertising metrics using information from aplurality of sources, such as those described in connection with datareception component 602. The processing system may include advertisementmedia selection component 626 that selects media, e.g., advertisementsor content, to be matched with content and to be directed to at leastone content viewing device using the advertising metrics generated at624 and an advertisement profile. The processing system may include acontent creation component 628 that identifies content to be createdbased on the advertising metrics generated at 624. For example, contentmay be identified that is predicted to provide a high ROI foradvertisers. The processing system may include an ROI derivationcomponent 630 that derives an ROI for adding the selected media to thecontent using the generated advertising metrics. The ROI derivationcomponent 630 may also use QoE information in the derivation. Theprocessing system may also include a pricing Derivation component 632configured to derive pricing for adding the selected media to thecontent. The pricing may be derived from the advertising metrics.

The processing system 614 may be implemented with a bus architecture,represented generally by the bus 602. The bus 602 may include any numberof interconnecting buses and bridges depending on the specificapplication of the processing system 614 and the overall designconstraints. The bus 602 links together various circuits including oneor more processors and/or hardware components, represented by theprocessor 604, the components 620, 622, 624, 626, 628, 630, 632, and thecomputer-readable medium/memory 606. The bus 602 may also link variousother circuits such as timing sources, peripherals, voltage regulators,and power management circuits, which are well known in the art, andtherefore, will not be described any further.

The processing system 614 may be coupled to at least one CDN 610involved in the transmission of content and/or advertisements to atleast one content viewing device 608. The CDN provides a means forcommunicating with various other apparatus over a transmission medium.Data may also be received over such a network for updating theadvertising metrics. The receiving component receives data from one ormore sources, extracts information from the received signal, andprovides the extracted information to the advertising metric generationcomponent. In addition, advertisement(s) and/or content may be sent fromprocessing system 614 for transmission over CDN 610 to content viewingdevice 608, e.g., from transmission component 622. The processing system614 includes at least one processor 604 coupled to a computer-readablemedium/memory 606. The at least one processor 604 is responsible forgeneral processing, including the execution of software stored on thecomputer-readable medium/memory 606. The software, when executed by theprocessor 604, causes the processing system 614 to perform the variousfunctions described supra for any particular system. Thecomputer-readable medium/memory 606 may also be used for storing datathat is manipulated by the processor 604 when executing software. Theprocessing system 614 further includes at least one of the components620, 622, 624, 626, 628, 630, 632. The components may be softwarecomponents running in the processor 604, resident/stored in the computerreadable medium/memory 606, one or more hardware components coupled tothe processor 604, or some combination thereof.

The processing system 614 may also include a communications interface,which allows software and data to be transferred between processingsystem 614 and external devices. Examples of such a communicationsinterface may include a modem, a network interface (such as an Ethernetcard), a communications port, a Personal Computer Memory CardInternational Association (PCMCIA) slot and card, etc. Software and datatransferred via communications interface may be in the form of signals,which may be electronic, electromagnetic, optical or other signalscapable of being received by communications interface. These signals maybe provided to communications interface via a communications path (e.g.,channel). This path may carry signals and may be implemented using anyof wire or cable, fiber optics, a telephone line, a cellular link, aradio frequency (RF) link and/or other communications channels.

The processing system 614 may be a component of a broadcast networksystem at the facility itself or as a cloud-based service whoseresources may be located at the facility or remotely.

In one configuration, the article of manufacture 600 includes means forgenerating a plurality of advertising metric, means for selecting anadvertisement, means for adding the advertisement to content fordelivery, means for deriving an ROI for adding a selected advertisementto the content, means for deriving pricing for adding the advertisementto the content, and means for creating content based on advertisingmetrics. The aforementioned means may be one or more of theaforementioned components of system 100, 200, 312 and/or the processingsystem 614 of the article of manufacture 600 configured to perform thefunctions recited by the aforementioned means.

The method, system, and computer program product of the presentdisclosure enable an individual to view real-time or customized mediaproductions. Additionally, the present disclosure enables a hostingfacility to automatically link advertisements or other types of messagesto a specific media production or show (or a specific showelement/story) by time, duration, and/or topic, or any other desiredcriteria.

FIG. 7 illustrates an example of a distributed advertisement network 700that comprises a plurality of advertisement management systems. Such asystem may include both a National, or larger regional, advertisingsystem 702, and affiliate advertising systems 704(a)-704(n). A Centralhost server 710 may reside at the facility for a national internetservice provider (ISP), such as AOL, AT&T, Verizon, or the like orcloud-based service such as Amazon AWS or Microsoft Azure or privatecloud and/or network operations center (NOC). In an embodiment, centralhost server 710 resides at the facility for a national informationservice provider that offers information content, such as news,entertainment, travel, history, art, business, education, science,health, recreation, careers, and/or the like. An information serviceprovider primarily hosts a national portal operating over the Internet,such as Verizon/AOL, MSN, Yahoo, Google, Facebook, and the like. Aninformation service provider also includes web sites operated by majornetworks (such as, CNN, MSNBC), local broadcasting networks,private/personal web sites or homepages, and the like.

Central host server 710 may include an advertising management databasefor tracking availabilities, demographics, pricing, social media, QoE,content metadata, historical advertisement metrics, and for generatingand updating advertising metrics, as discussed herein.

Central host server 710 may also include an advertisement database forstoring national advertisement media for national advertisementcampaigns and/or a media database for encoding and transmitting mediaproductions with linear advertising, e.g., as described in connectionwith FIG. 1.

Local host servers 720(a)-720(c) may be located within the localgeographical areas of a corresponding affiliate advertising system704(a)-704(n). As shown, an affiliate advertising system 704(a)-704(n)does not necessarily communicate with a corresponding local host server720(a)-720(c). Affiliate advertising systems 704(b) and 704(d), forexample, may communicate directly with central host server 710.

Local host servers 720(a)-720(c) may also include local databases andprocessing system similar to those for the central host server 710.

Each affiliate advertising system 704(a)-704(n) includes components ofsystem that enables the sale and distribution of advertising in itsrespective local or regional market. In other words, localadvertisements may be sold and managed by each affiliate advertisingsystem 720(a)-720(n).

Additionally, some affiliate advertising systems 704(a)-704(n) interactwith a central advertisements server or media server at central hostserver 710 for integrating and serving media and advertisementproductions to client-recipients, as described herein. Affiliateadvertising systems may communicate with both central host 710 and acorresponding local host in order to fill different ad avails atdifferent times.

Central host server 710 may periodically poll, update, and/orsynchronize information from the local host servers 720(a)-720(c) withthe central records. The periodic communications enable nationaladvertisement server to collect, verify, and modify information relatedto advertisement sales, reporting, accounting, trafficking, social mediainformation, QoE, user authorization, and/or the like, as describedherein, at a national level.

National advertising system 702 may provide national advertisements thatcan be selected and/or sold to the local markets managed by eachaffiliate advertising system 704(a)-704(n). In an embodiment, nationaladvertisements (from national advertising system 702 or central host710) may be served in open advertising spots by the traffic modules ofaffiliate advertising system 704(a)-704(n). Open advertising spots maybe defined by locations or time slots which are not sold locally byshow, show segment, topic, or the like. Affiliate advertising systems704(a)-704(n) may execute a media priority scheme, described in greaterdetail below, that enables local exclusive and target advertisements tobe served prior to national exclusive and targeted advertisements.National exclusive and targeted advertisements may be served beforelocal non-targeted advertisements. Local non-targeted advertisements maylikewise be served prior to national non-targeted advertisements, or canbe configured to be shared by rotating between local and nationalnon-targeting advertisements.

Media content may be live or as-live with a time shifted distribution.As-live content may include the same linear and non-linearadvertisements as the live content or may include at least one newadvertisement inserted according to the advertisement selectiondescribed herein.

By way of example and without limitation, the aspects of the presentdisclosure are presented with reference to systems and methods used toconfigure various components of a media production system that may beused for production of television programming or at sports events. Thevarious concepts presented throughout this disclosure may be implementedacross a broad variety of media production/advertisement systems.

It is understood that the specific order or hierarchy of blocks in theprocesses/flowcharts disclosed is an illustration of example approaches.Based upon design preferences, it is understood that the specific orderor hierarchy of blocks in the processes/flowcharts may be rearranged.Further, some blocks may be combined or omitted. The accompanying methodclaims present elements of the various blocks in a sample order, and arenot meant to be limited to the specific order or hierarchy presented.

The previous description is provided to enable any person skilled in theart to practice the various aspects described herein. Variousmodifications to these aspects will be readily apparent to those skilledin the art, and the generic principles defined herein may be applied toother aspects. Thus, the claims are not intended to be limited to theaspects shown herein, but is to be accorded the full scope consistentwith the language claims, wherein reference to an element in thesingular is not intended to mean “one and only one” unless specificallyso stated, but rather “one or more.” Combinations such as “at least oneof A, B, or C,” “at least one of A, B, and C,” and “A, B, C, or anycombination thereof” include any combination of A, B, and/or C, and mayinclude multiples of A, multiples of B, or multiples of C. Specifically,combinations such as “at least one of A, B, or C,” “at least one of A,B, and C,” and “A, B, C, or any combination thereof” may be A only, Bonly, C only, A and B, A and C, B and C, or A and B and C, where anysuch combinations may contain one or more member or members of A, B, orC. All structural and functional equivalents to the elements of thevarious aspects described throughout this disclosure that are known orlater come to be known to those of ordinary skill in the art areexpressly incorporated herein by reference and are intended to beencompassed by the claims. Moreover, nothing disclosed herein isintended to be dedicated to the public regardless of whether suchdisclosure is explicitly recited in the claims. No claim element is tobe construed under the provisions of 35 U.S.C. § 112, sixth paragraph,unless the element is expressly recited using the phrase “means for.”

What is claimed is:
 1. A system for delivering media to a contentviewing device to maximize quality of experience (QoE), the systemcomprising: an advertising metric generator configured to generate aplurality of advertising metrics based on data received from a pluralityof content viewing devices; a quality of playout determiner configuredto receive quality of playout information from at least one of theplurality of content viewing devices; a media selector configured toselect media for content directed to the at least one content viewingdevice based on the generated plurality of advertising metrics and basedon the received quality of playout information associated with the atleast one content viewing device to maximize a QoE of the selected mediaon the at least one content viewing device; and a media playoutcontroller configured to add the selected media to the content fordelivery to the at least one content viewing device, wherein thegenerated plurality of advertising metrics are based on at least one ofcontent analytics, advertising analytics, sales analytics, pricinganalytics, and social media analytics, and wherein the quality ofplayout information includes bitrate and buffering levels for thecontent to be transmitted and displayed on the at least one contentviewing device.
 2. The system of claim 1, wherein the advertising metricgenerator generates the plurality of advertising metrics based on firstdata originating from a social media application on a first device ofthe plurality of content viewing devices and second data originatingfrom a second device of the plurality of content viewing devices that isconnected to a packet based network.
 3. The system of claim 1, furthercomprising a media transmission controller configured to automaticallyselect at least one content delivery network (CDN) to deliver theselected media to the at least one content viewing device, the at leastCDN being selected to maximize the QoE at the at least one viewingdevice.
 4. The system of claim 3, further comprising a QoE determinerconfigured to determine a maximized QoE based on at least one of: aquality of service (QoS) performance measurement associated with aphysical transmission of the content and the selected media to the atleast one content viewing device, a performance measurement regardinginfrastructure involved with the physical transmission of the contentand the selected media to the at least one content viewing device, aperformance measurement regarding a content delivery network involvedwith the physical transmission of the content and the selected media tothe at least one content viewing device, a performance measurementregarding a website involved with the delivery of the content and theselected media to the at least one content viewing device, a performancemeasurement regarding a mobile application of the at least one contentviewing device involved with the delivery of the content and theselected media, and a performance measurement regarding reception of thecontent and the delivery media by the at least one content viewingdevice.
 5. The system of claim 3, further comprising a best streamprofile generated configured to generate a best stream profile based onthe determined maximized QoE and to automatically and dynamically changea routing of the selected media to at least one content viewing devicebased on the generated best stream profile.
 6. The system of claim 1,further comprising a bitrate selector configured to automatically selectthe bitrate for a data stream to deliver the selected media to the atleast one content viewing device to maximize the QoE at the at least onecontent viewing device.
 7. A system for delivering media to a contentviewing device to maximize quality of experience (QoE), the systemcomprising: an advertising metric generator configured to generate aplurality of advertising metrics based on data received from a pluralityof content viewing devices; a quality of playout determiner configuredto receive quality of playout information from at least one of theplurality of content viewing devices, wherein the quality of playoutinformation is based at least on a bitrate for content to be transmittedand displayed on the at least one content viewing device; a mediaselector configured to select media for content directed to the at leastone content viewing device based on the generated plurality ofadvertising metrics and based on the received quality of playoutinformation associated with the at least one content viewing device tomaximize a QoE of the selected media on the at least one content viewingdevice; and a media playout controller configured to add the selectedmedia to the content for delivery to the at least one content viewingdevice.
 8. The system of claim 7, wherein the generated plurality ofadvertising metrics are based on at least one of content analytics,advertising analytics, sales analytics, pricing analytics, and socialmedia analytics.
 9. The system of claim 7, wherein the quality ofplayout information is further based on at least one buffering level forthe content to be transmitted and displayed on the at least one contentviewing device.
 10. The system of claim 7, wherein the advertisingmetric generator generates the plurality of advertising metrics based onfirst data originating from a social media application on a first deviceof the plurality of content viewing devices and second data originatingfrom a second device of the plurality of content viewing devices that isconnected to a packet based network.
 11. The system of claim 7, furthercomprising a media transmission controller configured to automaticallyselect at least one content delivery network (CDN) to deliver theselected media to the at least one content viewing device, the at leastCDN being selected to maximize the QoE at the at least one viewingdevice.
 12. The system of claim 11, further comprising a QoE determinerconfigured to determine a maximized QoE based on at least one of: aquality of service (QoS) performance measurement associated with aphysical transmission of the content and the selected media to the atleast one content viewing device, a performance measurement regardinginfrastructure involved with the physical transmission of the contentand the selected media to the at least one content viewing device, aperformance measurement regarding a content delivery network involvedwith the physical transmission of the content and the selected media tothe at least one content viewing device, a performance measurementregarding a website involved with the delivery of the content and theselected media to the at least one content viewing device, a performancemeasurement regarding a mobile application of the at least one contentviewing device involved with the delivery of the content and theselected media, and a performance measurement regarding reception of thecontent and the delivery media by the at least one content viewingdevice.
 13. The system of claim 12, further comprising a best streamprofile generator configured to generate a best stream profile based onthe determined maximized QoE and to automatically and dynamically changea routing of the selected media to at least one content viewing devicebased on the generated best stream profile.
 14. The system of claim 7,further comprising a bitrate selector configured to automatically selectthe bitrate for a data stream to deliver the selected media to the atleast one content viewing device to maximize the QoE at the at least onecontent viewing device.
 15. A system for delivering advertising contentto a content viewing device based on quality of content playout dataassociated with the content viewing device, the system comprising: anadvertising content selector configured to select advertising content tobe transmitted to a content viewing device based on a plurality ofadvertising metrics associated with the advertising content and based onquality of content playout data associated with the content viewingdevice, the quality of content playout data comprising a detectedbitrate quality of content playout data associated with the contentviewing device; and a media playout controller configured to controlmedia playout of the selected advertising content to be transmitted tothe content viewing device based on the plurality of advertising metricsassociated with the advertising content and based on the detectedbitrate quality of content playout data associated with the contentviewing device.
 16. The system of claim 15, wherein the plurality ofadvertising metrics are based on at least one of content analytics,advertising analytics, sales analytics, pricing analytics, and socialmedia analytics.
 17. The system of claim 15, wherein the quality ofplayout data is further based on at least one buffering level for theselected advertising content to be transmitted and displayed on thecontent viewing device.
 18. The system of claim 15, further comprisingan advertising metric generator configured to generate the plurality ofadvertising metrics based on first data originating from a social mediaapplication on a first content viewing device and second dataoriginating from a second content viewing device that is connected to apacket based network.
 19. The system of claim 15, further comprising amedia transmission controller configured to automatically select atleast one content delivery network (CDN) based on a path of leastresistance to deliver selected advertising content to the contentviewing device, wherein the at least CDN is selected by the mediatransmission controller in order to maximize the QoE at the contentviewing device.
 20. The system of claim 19, further comprising a QoEdeterminer configured to determine a maximized QoE based on at least oneof: a quality of service (QoS) performance measurement associated with aphysical transmission of the selected advertising content to the contentviewing device, a performance measurement regarding infrastructureinvolved with the physical transmission of the selected advertisingcontent to the content viewing device, a performance measurementregarding a content delivery network involved with the physicaltransmission of the selected advertising content to the content viewingdevice, a performance measurement regarding a website involved with thedelivery of the selected advertising content to the content viewingdevice, a performance measurement regarding a mobile application of thecontent viewing device involved with the delivery of the selectedadvertising content, and a performance measurement regarding receptionof the selected advertising content by the content viewing device. 21.The system of claim 20, further comprising a best stream profilegenerator configured to generate a best stream profile based on thedetermined maximized QoE and to automatically and dynamically re-routethe selected advertising content to the content viewing device based onthe generated best stream profile.
 22. The system according to claim 15,further comprising a bitrate selector configured to automatically selectthe bitrate for a data stream to deliver the selected advertisingcontent to the content viewing device to maximize the QoE at the contentviewing device.